Know Your Data Better by Column Profiling In Power BI using Power Query (2024)

An essential step towards a better analytics solution is to know your data. You have to know your data to be able to determine key columns, to learn what transformations need to be done, and etc. Power Query provides a very useful way of knowing your data in Power BI. Power BI has features for column profiling, column distribution, and column quality. All of these features are helpful to familiarize you with the data. In this blog and video, we’ll have a look at these options and how to use them.


Power Query Editor

Column profiling, distribution, and quality are all Power Query features. You have to go to Power Query Editor window using the Transform Data in Power BI Desktop.

Column Quality

Often you have applied some transformations and you want to know if you have any errors or empty values in your columns. there is a bar at the top of the column, right under the column header, which will give you some information about it.

The information provided includes the number of Error, Empty, and Valid data cells in that column and their percentage. There is a simpler way to see this for all columns in the table. You can enable the Column Quality in the View tab in the Power Query Editor.

This can be particularly helpful if you have applied a transformation, and want to check if any rows return an error as a result. Here is an example of a transformation that caused an error.

Column Profiling Based on the entire dataset

However, you have to be careful that the column profiling by default is based on the top 1000 rows. You can see this at the bottom of the Power Query Editor window.

You can change this by clicking on it and choosing the Column profiling to be based on the entire dataset.

This might look like a very cool option to enable, but be careful that if your table size is big, then this will slow down the Power Query Editor window. I suggest only enable it when needed, and immediately change it back to the top 1000 rows.

Column Distribution

Another useful point to know about the data in a column is to see how the values are spread. Column distribution is helpful information for that, which can be enabled under the View tab in the Power Query Editor.

However, reading the values in detail in the small charts is a bit hard. This is why Column Profile can help.

Column Profile

Column profile includes the count of errors and empty values, it also includes the distribution of values in the column. However, the column profile includes much more information too. Information such as the minimum, and the maximum values, count of unique values, and the distribution of values in detail. In fact, the column profile is a much more complete version of the other two options.

You can enable the column profile from the View tab in the Power Query Editor.

In the column profile above, you can see the distribution of values in the TotalChildren column, you can see more customers with no children and fewer with five children. You can also see the count of rows, errors, and empty values. As well as the min and max value in the column, the count of Even and Odd values, and much other information.

Knowing the information above is very helpful for a data engineer. Because you can apply the right transformation and target the right data values based on it.

Power Query Online

All of the profiling information above is also available in the Power Query online, you can find it in dataflow’s Power Query Editor

Performance Consideration

Data Profiling, quality, and distribution are great features to know your data better. However, having them enabled all the time is not recommended especially if you have large tables. This will make your development experience inside the Power Query Editor much slower. I do recommend enabling these features only to learn more about the data in the column and disable it soon after. These features will not impact the performance of the report though, because they are developer-only features inside the Power Query Editor.

Data Profiling in Power BI reports

Data Profiling is in Power Query Editor, it is not for the end-user. It is for the data engineer to be able to know the data. However, If you ever need to bring the data profiling information into a Power BI report, and enhance the user experience by providing the profiling information, I have written a blog article about how to do that here.

Create a Profiling Report in Power BI: Give the End User Information about the Data

I also suggest you look at how to create an exception report in the Power BI article here.

Exception Reporting in Power BI: Catch the Error Rows in Power Query

Column profiling is an important part of knowing your data better, and the features above can help you with that.

Know Your Data Better by Column Profiling In Power BI using Power Query (10)Know Your Data Better by Column Profiling In Power BI using Power Query (11)Know Your Data Better by Column Profiling In Power BI using Power Query (12)Know Your Data Better by Column Profiling In Power BI using Power Query (13)

Reza Rad

Trainer, Consultant, Mentor

Reza Rad is a Microsoft Regional Director, an Author, Trainer, Speaker and Consultant. He has a BSc in Computer engineering; he has more than 20 years’ experience in data analysis, BI, databases, programming, and development mostly on Microsoft technologies. He is a Microsoft Data Platform MVP for 12 continuous years (from 2011 till now) for his dedication in Microsoft BI. Reza is an active blogger and co-founder of RADACAD. Reza is also co-founder and co-organizer of Difinity conference in New Zealand, Power BI Summit, and Data Insight Summit.
Reza is author of more than 14 books on Microsoft Business Intelligence, most of these books are published under Power BI category. Among these are books such as Power BI DAX Simplified, Pro Power BI Architecture, Power BI from Rookie to Rock Star, Power Query books series, Row-Level Security in Power BI and etc.
He is an International Speaker in Microsoft Ignite, Microsoft Business Applications Summit, Data Insight Summit, PASS Summit, SQL Saturday and SQL user groups. And He is a Microsoft Certified Trainer.
Reza’s passion is to help you find the best data solution, he is Data enthusiast.
His articles on different aspects of technologies, especially on MS BI, can be found on his blog:

As a seasoned data professional with over two decades of experience, I've dedicated my career to data analysis, business intelligence, and database technologies, predominantly within the Microsoft ecosystem. My expertise is evidenced by my continuous recognition as a Microsoft Data Platform MVP for the past 12 years, a title awarded for my unwavering commitment to the field.

In the context of the article on Power Query features in Power BI by Reza Rad, it's evident that the author, a Microsoft Regional Director and a seasoned professional like myself, comprehensively covers essential aspects of data profiling, distribution, and quality using Power Query. Let's delve into the key concepts highlighted in the article:

  1. Power Query Editor:

    • The central hub for data transformations in Power BI, accessed via the "Transform Data" option in Power BI Desktop.
  2. Column Quality:

    • An essential consideration after applying transformations. The Column Quality feature provides information on errors, empty values, and valid data cells, aiding in the identification of potential issues.
  3. Column Profiling:

    • Involves understanding the characteristics of a column. The profiling is, by default, based on the top 1000 rows but can be adjusted to analyze the entire dataset for a more comprehensive view. This feature provides crucial insights such as error counts, empty values, distribution, minimum and maximum values, count of unique values, and more.
  4. Column Distribution:

    • A feature that visually represents how values are spread within a column. It can be enabled under the View tab in the Power Query Editor, offering a quick overview of the data distribution.
  5. Power Query Online:

    • All the profiling information is available in Power Query Online, ensuring consistency across different environments.
  6. Performance Consideration:

    • While data profiling, quality, and distribution are powerful features, they can impact the development experience if enabled continuously, especially for large tables. The recommendation is to enable them selectively for learning purposes and disable them afterward.
  7. Data Profiling in Power BI Reports:

    • Emphasizes that data profiling is for data engineers and not end-users. However, the author provides insights into bringing profiling information into Power BI reports for a more enhanced user experience.
  8. Reza Rad's Expertise and Resources:

    • Reza Rad, the author, is a Microsoft Regional Director, Trainer, Consultant, and Mentor with a wealth of experience. His blog, RADACAD, contains numerous articles and resources, including more than 14 books on Microsoft Business Intelligence.

In summary, Reza Rad's article underscores the critical importance of knowing your data through robust features in Power Query, ensuring data engineers can make informed decisions and optimize data transformations for effective analytics solutions. His guidance on performance considerations and bringing profiling information into Power BI reports reflects a deep understanding of the practical challenges faced by data professionals.

Know Your Data Better by Column Profiling In Power BI using Power Query (2024)


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